Technology How visual AI can solve the challenge of testing...

How visual AI can solve the challenge of testing native mobile apps


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Consumers today live in a mobile-first world. According to research by App Annie“Consumers will have logged a record 3.8 trillion hours on their mobile phones and downloaded some 230 billion apps by 2021.”

Putting a further stamp on mobile dominance is that Americans now spend less time watching TV and spending money on average more time on their mobile phones.

As we all spend more time on our devices, technology leaders are under pressure to deliver more and better native mobile experiences faster than ever before. From banking to retail, healthcare to transportation, every industry is realizing that providing mobile app experiences is critical to survival.

Technology leaders have a challenging job ahead of them when it comes to delivering these experiences, especially as app quality, security, and business agility are measures of success. Using native mobile test automation strategies as part of the development process can ensure that these requirements are met and consumers are satisfied.

Below, we look at some of the key trends driving the need for native mobile app testing and quality assurance (QA). We also explore why adding artificial intelligence (AI) to the testing approach can quickly create next-generation mobile experiences for customers.

While there are many reasons and subjective circumstances that make native mobile app quality assurance more difficult than, say, web or desktop applications, the convergence of three trends adds a multiplier effect to the complexity of generating delightful mobile app experiences for consumers.

The vast world of mobile devices

Building a native mobile app has become a top priority for many companies to win over customers. However, the explosion of different mobile devices used by customers to access native mobile apps poses a huge challenge for QA and Agile software development teams. Not only do these teams need to account for new devices coming to market, but they need to be able to scale their mobile testing practices across multiple device types to validate apps on every device customers use.

According to Statistical, In 2021, the number of mobile devices active worldwide will reach almost 15 billion, compared to just over 14 billion in the previous year. The number of mobile devices is expected to reach 18.22 billion by 2025, an increase of 4.2 billion devices compared to 2020. Each new generation of devices between Apple, Samsung, Google and several other original equipment manufacturers (OEMs) means that test coverage needs to be expanded quickly and quickly adapt to market demand.

In addition, each device is expected to be different in terms of device resolutions/screen size, operating systems (and versions supported), screen orientations, scrolling views, and other factors. Usually this creates numerous development challenges that can slow down delivery cycles – and, even worse, reduce the quality of the mobile app.

Last but not least, testing native mobile apps is inherently more challenging than testing web applications. Not only is hardware installation expensive and cumbersome, but the software is also usually more difficult to handle.

Faster development cycles affect the scalability of mobile testing

Time to market to get new digital products, services and features into the hands of consumers is a competitive advantage. Ultimately, companies that ship more grow faster. However, QA and testing have created delays and bottlenecks for modern app development as the entire delivery lifecycle has merged with newer development tools, making building and deploying applications easier. Mobile app testing should be scaled concurrently to ensure faster delivery time.

There are many different approaches today to scale test automation for native mobile applications. Options range from running locally with virtual machines (simulators/emulators) or real machines to a local mobile network/lab to docker containers/virtual machines, or to remote cloud testing services.

Testing native mobile applications is a challenging endeavor as there are many moving parts and many points of failure. To execute successfully, everything must work in complete harmony. For example, running a single Appium test involves:

  • An Appium server with all required dependencies installed.
  • A mobile device or emulator/simulator.
  • Valid test code logic.
  • A compiled mobile application.
  • Application web service APIs active and stable (if applicable).

Not just “hoping for the best”

To scale tests across devices for validation needs across devices, prepare to introduce more points of failure for each device under test. A test on one device may run fine, but on another device it may fail for various unknown reasons. This can cause development and QA teams to spend an enormous amount of time investigating and debugging these errors to find the root cause.

Adding more devices to the mix means adding even more conditional logic to test code to accommodate these devices and their inherently different characteristics (screen size, operating system, orientation, locators, and other factors). All this adds more coded logic to a test suite or framework to maintain and eventually refactor in the future when the app changes.

For the above reasons, companies often cannot afford to extend their mobile test coverage across devices because test maintenance, more test issues, longer test execution times, or direct access to different devices is not possible. “Hope for the best” generally doesn’t work in these situations, and eventually the app experience suffers, causing customers to opt out.

Brand = mobile experience

It’s not enough for businesses to simply deliver mobile apps faster; apps must be visually and functionally perfect at all times. That’s because a company’s relationship with its customers is reflected in how the market perceives every aspect of its own brand experience, particularly on mobile, from identity to positioning, to UI/UX.

Take, for example, a mobile app for a retail company. If the “Add to cart” button doesn’t work or is hidden behind another button on certain screen sizes when the user tries to click, or if the text is off-center or difficult to read, this business can’t just miss out on one sale , but much before the bug is fixed.

Even worse, it could lose potential customers and brand advocates forever. This becomes even more important when it comes to industries such as healthcare, banking and insurance, where functional and visual issues with an app can have serious consequences for end users, which will not be tolerated.

If you don’t believe that visual defects, poor UI/UX experiences, and other functional flaws on a mobile website or application can tarnish a brand’s reputation in seconds, consider the following metrics collected by

  • 88% of users are less likely to return to a website after a bad user experience.
  • Mobile users are five times more likely to abandon a task if the website is not optimized for mobile.
  • 80% of all internet users own a smartphone.
  • 53% of mobile users leave websites in just three seconds.
  • 90% of users have stopped using an app due to poor performance.
  • Only 55% of companies are currently conducting user experience testing.

And PWC found that 32% of customers would leave a brand they love after just one bad experience.

Why visual AI is needed for testing and improving native mobile apps

Companies are trying different approaches to address these challenges, including “shifting to the left,” where the development team takes on more testing responsibilities, and using AI to speed up the testing process and achieve higher coverage.

But visual AI is the technology that will bring mobile apps to the next generation of customer experiences and help ensure brand loyalty. Software engineering leaders and development teams can leverage visual AI to better equip themselves to meet the growing challenges of mobile app testing through enhanced quality technical tactics and strategies.

Without visual AI, the number of UI/UX permutations for a mobile app is overwhelming and impossible for development and QA teams to navigate. Fortunately, there is a new technological approach, powered by visual AI, to validate a native mobile application asynchronously, in parallel, and easily across many different devices in a single test run (versus tens or hundreds).

This means visual AI powered native mobile tests can provide instant access and validation to a huge inventory of mobile devices with different screen sizes/viewports and operating systems. And because it’s asynchronous, teams don’t wait for the device to connect or test results, freeing up tests to run as quickly as possible.

The promise of visual AI

Today, visual AI-powered mobile testing technologies can outperform traditional in-house device testing farms and traditional real-device testing clouds; tests that took 8 to 10 minutes are now performed in less than two minutes.

Engineering teams that need to quickly deliver high-quality mobile apps use visual AI-powered technology to reduce test execution time by up to 90%. In addition, technology teams using these technologies do not require extensive training. Users can get started in minutes. Using advanced computer vision AI algorithms already built in, they can run automated tests on simulated mobile devices in seconds. Teams using this technology report significantly higher test coverage than the benchmark and faster release speed.

At the end of the day, knowing that visual and functional decline can be spotted immediately with visual AI across all variations of mobile devices gives peace of mind to those responsible for ensuring a mobile user experience is exactly as intended for the customer.

The end goal for any company dealing with the challenges of mobile app delivery and brand experience is to future-proof its approach so that native mobile app testing can finally keep pace with mobile app development. With visual AI, it is now possible to continuously ship mobile apps with the speed and accuracy not possible with traditional mobile testing techniques.

Moshe Milman is co-founder and COO at Applitools.

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